Research on AI-Based Smart Finance Innovation Models and Their Impact Mechanisms

With the rapid advancement of artificial intelligence (AI) technology, smart finance is undergoing profound transformation. This paper systematically investigates three core applications of AI in the financial sector: in risk management, machine learning is used to integrate multi-source data, significantly improving the accuracy of credit assessment and the effectiveness of fraud detection; in investment decision-making, alternative data analytics reshape the paradigm of fundamental research; and in customer service, AI enables intelligent and personalized user experiences. The study also analyzes the symbiotic relationship between the digital economy and smart finance, revealing how the restructuring of data elements reshapes the financial value chain. At the level of innovation models, this paper focuses on the practical pathways and challenges of robo-advisory, digital lending, blockchain finance, and financial cloud services. The findings show that in China, current AI applications in finance still face bottlenecks such as data privacy concerns, algorithmic opacity, and lagging regulation, particularly in emerging areas like digital lending and robo-advisory.

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Publication Details

Journal
Advances in Economics and Management Research
Published
2025-07-26
DOI
https://doi.org/10.56028/aemr.14.1.711.2025
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on AI-Based Smart Finance Innovation Models and Their Impact Mechanisms

Junyuan Chen
Advances in Economics and Management Research
FinTech, Crowdfunding, Digital Finance
article

Research on AI-Based Smart Finance Innovation Models and Their Impact Mechanisms

Junyuan Chen
article en

Abstract

With the rapid advancement of artificial intelligence (AI) technology, smart finance is undergoing profound transformation. This paper systematically investigates three core applications of AI in the financial sector: in risk management, machine learning is used to integrate multi-source data, significantly improving the accuracy of credit assessment and the effectiveness of fraud detection; in investment decision-making, alternative data analytics reshape the paradigm of fundamental research; and in customer service, AI enables intelligent and personalized user experiences. The study also analyzes the symbiotic relationship between the digital economy and smart finance, revealing how the restructuring of data elements reshapes the financial value chain. At the level of innovation models, this paper focuses on the practical pathways and challenges of robo-advisory, digital lending, blockchain finance, and financial cloud services. The findings show that in China, current AI applications in finance still face bottlenecks such as data privacy concerns, algorithmic opacity, and lagging regulation, particularly in emerging areas like digital lending and robo-advisory.

Advances in Economics and Management ResearchVol. 14(1)
Openalex Percentile: Top 68%
FinTech, Crowdfunding, Digital Finance
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